Machine Learning – Linear Regression Quiz Answers

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Q1) Based on the regression equation, with every 1000 unit increase in income, the monthly revenue will:

• Decrease by 2.2 unit
• Decrease by 81.6 unit
• Increase by 2.2 unit
• Increase by 81.6 unit

Q2) Looking at the Least Square Method plot, what will be your conclusion?

• The data is random
• There is a linear relation between the two variables
• The data has autocorrelation
• The data is normal

Q3) Do you agree the fact that the estimate of the target variable is unbiased, i.e. average residuals is almost zero?

• Don’t Agree
• Agree

Q4) In this simulation we tried to predict Annual Income of a customer through his/her average monthly revenue. True or False?

• FALSE
• TRUE

Q5) What is the percentage of variation explained by the model?(Mark the closest value)

• 40%
• 39%
• 60%
• 61%

Q6) Given other factors unchanged, if a flight departs 10 mins late, the flight’s expected delay in arrival is:

• Delayed by 9 seconds
• Early by 9 seconds
• Delayed by 9 minutes
• Early by 9 minutes

Q7) Find the odd one out (based on variable significance):

• Departure Delay
• Taxi Out Time
• Air Time
• Taxi In Time

Q8) The most important variable to predict arrival delay (as per the model) is:

• Air Time
• Mid of Week Flag
• Distance
• Departure Delay

Q9) Find the odd one out (based on variable type):

• Taxi Out Time
• Distance
• Departure Delay
• Air Time

Q10) What is the MAPE of the model? (Select the closest value)

• 0.308
• 0.196
• 0.087
• 0.219

Q11) Did the model rank ordered with respect to predicted value of average fare?

• TRUE
• FALSE

Q12) What percentage of observations have absolute percentage deviation less than 25%? (Select the closest value)

• 0.59
• 0.38
• 0.62
• 0.21

Q13) How much improvement we got from using the variable transformation? (Mark the closest value)

• R-square dropped little more than 1%
• R-square increased little less than 1%
• R-square increased little more than 1%
• R-square dropped little less than 1%

Q14) From the final model what we can infer about the predictor Retail Establishment?

• It has an insignificant impact at Retail Sales
• It has a positive directional impact at Retail Sales
• It has a negative directional impact at Retail Sales
• None of the above

Q15) From the final model what we can infer about the predictor Income?

• It has a negative directional impact at Retail Sales
• It has an insignificant impact at Retail Sales
• None of the above
• It has a positive directional impact at Retail Sales

Q16) Which variable did you identified to cause overfitting in the model?

• Market-share of lowest price airline
• Average Weekly Passenger
• Market-share of leading airline
• Average Fare of Leading Airline

Q17) What was the drop in model R-square post removal of overfitting? (select the closest one)

• 43% from 97%
• 44% from 96%
• 43% from 96%
• 44% from 97%

Q18) Which variable came insignificant at 99% at the first run?

• Lowest Price
• None of the above
• Average Weekly Passengers
• Distance